Generalized from Karpathy's autoresearch. Same loop, any domain.
An AI agent runs an infinite hill-climbing loop: modify → run → measure → keep or revert → repeat. No human in the loop. Wake up to a TSV of completed experiments.
Generalized from Karpathy's autoresearch. Same loop, any domain.
An AI agent runs an infinite hill-climbing loop: modify → run → measure → keep or revert → repeat. No human in the loop. Wake up to a TSV of completed experiments.
| You are a GPT created by a user, and your name is Tutor Me. Note: GPT is also a technical term in AI, but in most cases if the users asks you about GPTs assume they are referring to the above definition. | |
| Here are instructions from the user outlining your goals and how you should respond: | |
| You are a tutor that always responds in the Socratic style. I am a student learner. Your name is Khanmigo Lite. You are an AI Guide built by Khan Academy. You have a kind and supportive personality. By default, speak extremely concisely at a 2nd grade reading level or at a level of language no higher than my own. | |
| If I ask you to create some practice problems for them, immediately ask what subject I’d like to practice, and then practice together each question one at a time. | |
| You never give the student (me) the answer, but always try to ask just the right question to help them learn to think for themselves. You should always tune your question to the knowledge of the student, breaking down the problem into simpler parts until |
| /* First, our Schroeder-Moorer filtered-feedback comb-filters | |
| * | |
| * @param {string} name – for identifying our feedback taps | |
| * @param {number} size – for defining our feedback tap lengths | |
| * @param {Node | number} feedback: [0, 1) – how long the reverb should ring out | |
| * @param {Node | number} damping : [0, 1) – pole position of the lowpass filter | |
| * @param {Node} xn – input signal to filter | |
| * | |
| * @see https://ccrma.stanford.edu/~jos/pasp/Feedback_Comb_Filters.html | |
| */ |
| #!/bin/bash | |
| # Description: Split an m4b into its chapters. No recoding is done, just splitting | |
| # Usage: m4b_split.sh $input_file $output_dir/ | |
| # Requires: ffmpeg, jq | |
| # Author: Hasan Arous | |
| # License: MIT | |
| in="$1" | |
| out="$2" | |
| splits="" |
The idea is nice:
| <!--XSL style sheet to convert EESCHEMA XML Partlist Format to grouped CSV BOM Format | |
| Copyright (C) 2014, Wolf Walter. | |
| Copyright (C) 2013, Stefan Helmert. | |
| Copyright (C) 2018, Kicad developers. | |
| Copyright (C) 2019, arturo182. | |
| GPL v2. | |
| Functionality: | |
| Generation of JLCPCB PCBA compatible BOM |
| !pip install fastai | |
| !apt-get -qq install -y libsm6 libxext6 && pip install -q -U opencv-python | |
| import cv2 | |
| from os import path | |
| from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag | |
| platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()) | |
| accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu' | |
| !pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.3.0.post4-{platform}-linux_x86_64.whl torchvision |
The proposal you’re about to read is not just a proposal. We have a working implementation of almost everything we discussed here. We encourage you to checkout and build our branch: our fork, with the relevant branch selected. Building and using the implementation will give you a better understanding of what using it as a developer is like.
Our implementation ended up differing from the proposal on some minor points. As our last action item before making a PR, we’re writing documentation on what we did. While I loathe pointing to tests in lieu of documentation, they will be helpful until we complete writing docs: the unit tests.
This repo also contains a bundled version of npm that has a new command, asset. You can read the documentation for and goals of that comma
| var IMAGE_MIME_REGEX = /^image\/(p?jpeg|gif|png)$/i; | |
| var loadImage = function (file) { | |
| var reader = new FileReader(); | |
| reader.onload = function(e){ | |
| var img = document.createElement('img'); | |
| img.src = e.target.result; | |
| var range = window.getSelection().getRangeAt(0); | |
| range.deleteContents(); |